Signal mismatches in electronic devices, including gain, phase, and DC-offset mismatches, are caused by many different factors, and are generated primarily in the analog electronics of a system, such as amplifiers, analog-to-digital converters, digital-to-analog converters, or delay elements. These devices tend to introduce mismatches that have undesirable effects, such as distortion, that limit the performance of systems. Mismatches can severely limit the cancellation of signals, which is critical in many applications such as beamforming, nonlinear distortion compensation, and analog-to-digital conversion.
One particularly demanding application is a high-speed, high-resolution analog-to-digital converter (ADC) that uses an array of ADCs to increase the speed and resolution of the conversion operation. Signal mismatches between converters, such as gain mismatch, phase mismatch, or DC-offset, often prohibit existing parallel architectures, such as Time-Interleaving-based architectures, from achieving high resolution. Even a small drift in the signal mismatches can significantly limit system performance. Signal mismatches can be caused by a number of different factors, including imprecise analog component values, line-length mismatches, and other variations in the analog front-end electronics. To achieve high resolution (e.g., greater than 12 bits), conventional parallel approaches, such as Time-Interleaving, require analog phase matching performance on the order of femtoseconds and gain matching better than 0.1%, which are extremely challenging constraints to achieve.
Conventional mismatch compensation techniques often require the injection of calibration tones or switching the unit into an off-line mode for calibration. Conventional architectures often do not track mismatches that change over time or other environmental conditions, such as airflow causing a temperature gradient. For these reasons, the performance, including speed or resolution, for example, of such architectures, is therefore limited.
FIG. 1 is a block diagram of a conventional matching system with offline calibration. A conventional approach to calibrating a system with mismatches 50 includes a gain and phase adjustment unit 27 and an offline calibrator 28. During normal operation of the system with mismatches 50, the system with mismatches 50 receives input signals 10, and the gain and phase of the unmatched signals 20 are adjusted by the gain and phase adjustment unit 27 to help minimize the mismatches in the output signals 31.
During calibration, however, the normal operation of the system is interrupted by calibration switches 29 that change the inputs to the system with mismatches with mismatches 50 to calibration signals 15. In a calibration mode, the calibration signals are applied to the system with mismatches 50, and the resulting calibration monitor signals 16 are analyzed by the offline calibrator 28. The offline calibrator 28, in turn, estimates the gain and phase mismatches of the calibration monitor signals 16, and applies gain and phase mismatch parameters 41 to the gain and phase adjustment unit 27 to compensate for mismatches in the applied mismatched signals 20.
Another limitation of the conventional approaches is that the offline calibrator 28 does not characterize the variation of the mismatches with respect to the frequency of the input signals 10. Instead, the offline calibrator 28 provides fixed gain and phase mismatch parameters 41 to the gain and phase adjustment unit 27 in response to calibration signals 15. Further, the gain and phase adjustment unit 27 compensates input signals with varying frequencies with a constant gain and phase shift. Thus the conventional matching system does not accurately compensate for varying mismatches when input signals 10 have varying frequency.
A conventional approach to system monitoring uses a monitoring signal that includes tones with frequencies that are not intended to overlap those frequencies in use by the system. While this approach does not interrupt the normal operation of the system, it does, however, require advanced knowledge of the frequency content of the signals being processed by the system and limits the usable frequency range of the system. In addition, system performance is only characterized at the few frequencies used by the monitoring tone or tones. The monitoring tones may also interfere with the normal, accurate functioning of the system, since the tones may have frequency content that is near frequencies in use by the system.
Another limitation of conventional calibration methods is that they generally do not consider measurement history for updating the compensation processing, but rather they simply employ a most recent measurement to update the compensation. This approach fails to provide stable system performance because a one-time glitch or inaccurate measurement can cause a miscalibration that significantly degrades system performance until such a time that a more accurate measurement can be made. Also, for applications such as frequency-hopping where frequency changes are very rapid, this type of calibration cannot update itself quickly enough to track mismatches that are different with respect to input frequency. By the time the mismatches have been measured and corrected for a particular frequency, the frequency of the input signal may have already changed.